本文選題：認(rèn)知無線電 + 頻譜預(yù)測(cè)　； 參考：《北京交通大學(xué)》2014年博士論文

【摘要】：頻譜感知、頻譜決策、頻譜共享、頻譜搬移是認(rèn)知無線電技術(shù)的四大功能。次級(jí)用戶通過頻譜感知發(fā)掘頻譜空穴,并通過頻譜決策、頻譜共享、頻譜搬移三個(gè)功能對(duì)發(fā)掘的頻譜空穴加以利用。傳統(tǒng)的頻譜感知、頻譜決策、頻譜共享和頻譜搬移通常造成較大的處理時(shí)延、反應(yīng)時(shí)延、以及能量消耗。為了解決上述問題,研究人員提出了頻譜預(yù)測(cè)技術(shù),利用不同的方法實(shí)現(xiàn)對(duì)未來時(shí)刻的頻譜狀態(tài)的預(yù)測(cè)。已有工作尚未針對(duì)如何利用次級(jí)用戶之間的合作,改善未來時(shí)刻頻譜狀態(tài)預(yù)測(cè)準(zhǔn)確率這一問題展開研究。此外,如何預(yù)測(cè)更多的頻譜參數(shù),并充分利用這些參數(shù)進(jìn)一步改善認(rèn)知無線電網(wǎng)絡(luò)的整體性能,也是頻譜預(yù)測(cè)技術(shù)研究領(lǐng)域有待解決的難點(diǎn)之一。本論文針對(duì)上述難點(diǎn)問題,對(duì)認(rèn)知無線電網(wǎng)絡(luò)中的頻譜預(yù)測(cè)技術(shù)進(jìn)行深入詳細(xì)的研究。主要內(nèi)容及創(chuàng)新點(diǎn)包括： 1.研究了認(rèn)知無線電網(wǎng)絡(luò)中的協(xié)作頻譜狀態(tài)預(yù)測(cè)問題。認(rèn)識(shí)到已有的單個(gè)次級(jí)用戶單獨(dú)進(jìn)行的本地頻譜狀態(tài)預(yù)測(cè)方法預(yù)測(cè)準(zhǔn)確率有限的問題,充分利用次級(jí)用戶之間自發(fā)的合作,提出一種新的協(xié)作頻譜狀態(tài)預(yù)測(cè)方法,改善頻譜狀態(tài)預(yù)測(cè)的準(zhǔn)確率。具體而言： 1)將次級(jí)用戶之間的合作過程建模為一個(gè)合作博弈過程,并基于合作博弈理論以最大化次級(jí)用戶的頻譜預(yù)測(cè)準(zhǔn)確率為目標(biāo)提出了一種新的合作組形成算法。每個(gè)合作組內(nèi)選擇一個(gè)次級(jí)用戶擔(dān)任首領(lǐng),負(fù)責(zé)匯總組內(nèi)其他用戶的本地頻譜狀態(tài)預(yù)測(cè)結(jié)果,并通過數(shù)據(jù)融合獲得協(xié)作頻譜狀態(tài)預(yù)測(cè)結(jié)果。 2)將設(shè)計(jì)的協(xié)作頻譜狀態(tài)預(yù)測(cè)方法擴(kuò)展到任意多個(gè)初級(jí)用戶任意多個(gè)次級(jí)用戶構(gòu)成的認(rèn)知無線電網(wǎng)絡(luò)中,改善算法的普適性。基于任務(wù)分配的思想,將次級(jí)用戶分類,每一類用戶只對(duì)一個(gè)初級(jí)用戶的授權(quán)頻譜進(jìn)行協(xié)作頻譜狀態(tài)預(yù)測(cè),有效降低了多個(gè)初級(jí)用戶場(chǎng)景下協(xié)作頻譜狀態(tài)預(yù)測(cè)的復(fù)雜度。 2.研究了基于頻譜狀態(tài)持續(xù)時(shí)間預(yù)測(cè)的次級(jí)用戶頻譜感知間隔優(yōu)化方法。傳統(tǒng)的頻譜感知技術(shù)要求次級(jí)用戶在每個(gè)時(shí)隙的開始階段進(jìn)行一次頻譜感知。而真實(shí)頻譜使用數(shù)據(jù)則表明任一頻譜狀態(tài)都以一定概率持續(xù)若干時(shí)隙。在上述背景下,次級(jí)用戶的最優(yōu)頻譜感知間隔,即次級(jí)用戶兩次頻譜感知之間間隔多少個(gè)時(shí)隙,成為一個(gè)值得研究的課題。具體的研究包括： 1)次級(jí)用戶用一個(gè)隱馬爾科夫模型來描述頻譜狀態(tài)的變化規(guī)律,并通過分析該模型預(yù)測(cè)頻譜狀態(tài)的持續(xù)時(shí)間。 2)基于對(duì)頻譜狀態(tài)持續(xù)時(shí)間的預(yù)測(cè)結(jié)果,進(jìn)一步預(yù)測(cè)次級(jí)用戶采用某一頻譜感知間隔時(shí)將會(huì)錯(cuò)過的傳輸機(jī)會(huì)、對(duì)初級(jí)用戶造成的干擾、以及次級(jí)用戶網(wǎng)絡(luò)的吞吐量等指標(biāo)。針對(duì)每個(gè)指標(biāo),基于Sigmoid函數(shù)設(shè)計(jì)次級(jí)用戶的滿意度函數(shù)。綜合考慮各個(gè)指標(biāo)的滿意度,次級(jí)用戶能夠確定最優(yōu)的頻譜感知間隔。 3.設(shè)計(jì)了基于頻譜質(zhì)量預(yù)測(cè)的動(dòng)態(tài)頻譜接入方案�？紤]到傳統(tǒng)的隨機(jī)動(dòng)態(tài)頻譜接入方案忽略了接入不同質(zhì)量的頻譜會(huì)帶來不同的網(wǎng)絡(luò)性能這一問題,提出一種新型的基于頻譜質(zhì)量預(yù)測(cè)的動(dòng)態(tài)頻譜接入方案,使得次級(jí)用戶能夠優(yōu)先選擇高質(zhì)量頻譜進(jìn)行接入,從而有效改善網(wǎng)絡(luò)性能。具體而言： 1)次級(jí)用戶用非平穩(wěn)隱馬爾科夫模型準(zhǔn)確的描述頻譜狀態(tài)的變化過程及自身的頻譜感知過程,并通過貝葉斯推斷估計(jì)非平穩(wěn)隱馬爾科夫模型的參數(shù)。 2)通過分析貝葉斯推斷獲得的非平穩(wěn)隱馬爾科夫模型參數(shù),次級(jí)用戶對(duì)頻譜的空閑時(shí)間長(zhǎng)度、次級(jí)用戶在頻譜上進(jìn)行頻譜感知的檢測(cè)概率和誤警概率進(jìn)行預(yù)測(cè)。綜合上述指標(biāo),定義新型的頻譜質(zhì)量評(píng)價(jià)指標(biāo)從而實(shí)現(xiàn)次級(jí)用戶對(duì)頻譜質(zhì)量的預(yù)測(cè)。 3)設(shè)計(jì)一種新型的基于頻譜質(zhì)量預(yù)測(cè)的動(dòng)態(tài)頻譜接入方案。方案中,次級(jí)用戶依據(jù)頻譜質(zhì)量預(yù)測(cè)結(jié)果對(duì)所有頻譜進(jìn)行排序。當(dāng)需要接入頻譜時(shí),次級(jí)用戶優(yōu)先選擇質(zhì)量較高的頻譜進(jìn)行頻譜感知和接入。
[Abstract]:Spectrum sensing, spectrum decision, spectrum sharing, and spectrum moving are the four major functions of cognitive radio. Secondary users discover spectrum holes through spectrum sensing, and use the three functions of spectrum decision, spectrum sharing and spectrum removal to exploit spectrum holes. Traditional spectrum sensing, spectrum decision, spectrum sharing and spectrum removal In order to solve the above problems, researchers have proposed spectrum prediction technology to predict the spectrum state of the future time by using different methods. In addition, how to predict more spectrum parameters and make full use of these parameters to further improve the overall performance of cognitive radio networks is one of the difficulties to be solved in the field of spectrum prediction technology. This paper aims at the above difficulties to predict the spectrum of spectrum in cognitive radio networks. The main contents and innovations include:
1. the problem of cooperative spectrum state prediction in cognitive radio networks is studied. Recognizing the problem that the local spectrum state prediction method of individual secondary users has limited prediction accuracy, we make full use of the spontaneous cooperation between secondary users, and propose a new cooperative spectrum state prediction method to improve the spectrum state precondition. The accuracy of the test.
1) the cooperation process between secondary users is modeled as a cooperative game process, and a new cooperative group formation algorithm is proposed based on the cooperative game theory to maximize the frequency prediction accuracy of the secondary users. In each group, a secondary user is selected as the head leader to collect the local spectrum of other users in the group. The state prediction results are obtained and the result of cooperative spectrum state prediction is obtained through data fusion.
2) the proposed cooperative spectrum state prediction method is extended to the cognitive radio network composed of any multiple primary users, and the universality of the algorithm is improved. Based on the task allocation idea, the secondary users are classified, and each class of users can only predict the cooperative spectrum state of the authorized spectrum of a primary user. The efficiency of cooperative spectrum state prediction in multiple primary user scenarios is reduced.
2. the secondary user spectrum sensing interval optimization method based on the spectrum state duration prediction is studied. The traditional spectrum sensing technology requires secondary users to perform a spectrum sensing at the beginning of each slot. And the real spectrum data shows that any spectrum state continues to a certain number of slots at a certain probability. At the same time, the optimal spectrum sensing interval of secondary users, that is, how many time slots interval between secondary users' two spectrum sensing, has become a subject worthy of study.
1) secondary users use a hidden Markov model to describe the change of spectrum state, and predict the duration of spectrum state by analyzing the model.
2) based on the prediction results of the duration of the spectrum status, we can further predict the transmission opportunities that the secondary users will miss, the interference to the primary users and the throughput of the secondary user network, and design the satisfaction function of the secondary users based on the Sigmoid function. Considering the satisfaction of each index, secondary users can determine the optimal spectrum sensing interval.
3. the dynamic spectrum access scheme based on the spectrum quality prediction is designed. Considering that the traditional random dynamic spectrum access scheme ignores the different network performance with different quality of the spectrum, a new dynamic spectrum access scheme based on the spectrum quality prediction is proposed, so that the secondary users can be selected first. The high quality spectrum is accessed to effectively improve network performance.
1) the secondary user accurately describes the change process of the spectrum state and its spectrum sensing process using the non-stationary hidden Markov model, and estimates the parameters of the nonstationary hidden Markov model by Bayesian inference.
2) by analyzing the parameters of the non-stationary hidden Markov model obtained by Bayesian inference, the secondary user has the free time length of the spectrum, the secondary user predicts the detection probability and the false alarm probability of the spectrum perception on the spectrum, and defines the new spectrum quality evaluation index to realize the secondary user's spectrum quality. Prediction of quantity.
3) a new dynamic spectrum access scheme based on spectrum quality prediction is designed. In the scheme, the secondary user sort all the spectrum according to the spectrum quality prediction results. When the spectrum is needed, the secondary user selects the high quality spectrum for spectrum sensing and joining.
【學(xué)位授予單位】：北京交通大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2014
【分類號(hào)】：TN925

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